Functional enrichment analysis of deregulated long non-coding RNAs in cancer based on their genomic neighbors

Olgun, Gülden and Taştan, Öznur (2020) Functional enrichment analysis of deregulated long non-coding RNAs in cancer based on their genomic neighbors. In: 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), Virtual (Accepted/In Press)

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Abstract

The dysregulation of long non-coding RNAs’ (lncRNAs) expressions has been implicated in cancer. Since most of the lncRNAs’ are not functionally characterized well, investigating the set of perturbed lncRNAs are is challenging. Existing methods that inspect lncRNAs functionally rely on the coexpressed coding genes, which are far better characterized functionally. LncRNAs can be known to act as transcriptional regulators; they may activate or repress the neighborhood’s coding genes on the genome. Based on this, in this work, we aim to analyze the deregulated lncRNAs in cancer by taking into account their ability to regulate nearby loci on the genome. We perform functional analysis on differentially expressed lncRNAs for 28 different cancers considering their adjacent coding genes. We identify that some deregulated lncRNAs are cancer-specific, but a substantial number of lncRNAs are shared across cancers. Next, we assess the similarities of the cancer types based on the functional enrichment of the deregulated lncRNA sets. We find some cancers are very similar in the functions and biological processes related to the deregulated lncRNAs. We observe that some of the cancers for which we find similarity can be linked through primary, metastatic site relations. We investigate the similarity of enriched functional terms for the deregulated lncRNAs and the mRNAs. We further assess the enriched functions’ similarity to the functions and processes that the known cancer driver genes take place. We believe that our methodology help to understand the impact of the lncRNAs in cancer functionally.
Item Type: Papers in Conference Proceedings
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Biological Sciences & Bio Eng.
Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng.
Faculty of Engineering and Natural Sciences
Depositing User: Öznur Taştan
Date Deposited: 27 Sep 2020 17:17
Last Modified: 26 Apr 2022 09:37
URI: https://research.sabanciuniv.edu/id/eprint/41114

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